彩色图像分割的 Hill-Climbing 算法

Hill-Climbing Algorithm for Color Image Segmentation. % IDX = KMEANS(X, K) partitions the points in the N-by-P data matrix % X into K clusters. This partition minimizes the sum, over all % clusters, of the within-cluster sums of point-to-cluster-centroid % distances. Rows of X correspond to points, columns correspond to % variables. KMEANS returns an N-by-1 vector IDX containing the % cluster indices of each point. By default, KMEANS uses squared % Euclidean distances.